Senior Data Standards Engineer - Evinova

Evinova is a health tech company purpose-built to transform how clinical trials are designed, executed, and understood. Our platform powers data analytics and trial oversight across entire sponsor portfolios, at global scale.

We operate at the intersection of life sciences and technology. We move fast, take smart risks, and build things that genuinely matter.

As a Senior Data Standards Engineer at Evinova, you'll architect and operate the automated pipelines that keep our Data Platform current with evolving clinical dictionaries and reference datasets - from CDISC controlled terminology releases to FHIR value sets and ICH M11 updates. Your work will be the backbone of how clinical study protocols (CSPs) are interpreted, designed and monitored across Evinova's expanding customer portfolio.

This is a senior engineering role with genuine scope: you'll set technical direction, drive automation-first thinking, and mentor a high-calibre team - all in a fast-moving health tech environment where your decisions directly influence how medicines reach patients.

What if every time a clinical data standard was updated, your platform simply knew - and adapted automatically, with no human intervention required? That's the challenge you'll own.

You'll join a high-performing, globally distributed Data Platform team. We work in agile/scrum cycles, deploy on AWS, and hold ourselves to engineering standards that support both regulated (GxP) and innovation-track workstreams., Your primary mission is eliminating manual effort from the standards lifecycle. You will:

• Design and own fully automated ELT/ETL pipelines that detect, ingest, validate, and publish new releases of clinical dictionaries (e.g., MedDRA, WHO Drug, SNOMED CT, CDISC CT, NCI Thesaurus) without human intervention

• Build event-driven and scheduled pipeline architectures on AWS (Lambda, Step Functions, Glue, S3, EventBridge) that react to upstream standard releases and propagate changes downstream automatically

• Implement automated versioning and change detection so downstream consumers always know what changed, what's new, and what's been deprecated - and can act on it programmatically

Clinical Standards Architecture

• Apply deep expertise in USDM, ICH M11, FHIR, and CDISC (SDTM/ADaM/CDASH) to define canonical schemas, mapping strategies, and versioning models for clinical dictionaries and controlled vocabularies

• Design optimized data stores (relational, columnar, graph as appropriate) for serving clinical reference data at query speed - including schema design, indexing, partitioning, and performance tuning

• Model how terminology, code lists, and controlled vocabularies relate across standards and internal systems, enabling consistent coding and reporting across all clinical workflows

AI & Machine Learning Integration

• Implement AI-assisted mapping between dictionaries and source systems - surfacing high-confidence automated mappings and flagging exceptions for review

• Deploy ML-based anomaly detection to identify inconsistencies, unexpected changes, or quality issues across ingested standards data

• Explore and productionize LLM-assisted tools for standards interpretation, change summarization, and intelligent workflow automation

Technical Leadership & Stakeholder Influence

• Set engineering best practices for the data standards domain - pipeline design patterns, testing strategies, infrastructure-as-code, observability, and documentation standards

• Serve as the technical authority on clinical data standards for the Data Platform team, providing guidance to clinical operations, data management, biostatistics, safety, and regulatory functions

• Communicate complex standards and data engineering concepts clearly to both technical and non-technical audiences - from engineers to clinical leads to senior leadership

• Mentor and upskill team members, fostering a culture of automation-first engineering and continuous improvement

Data Engineering & Automation

• 8+ years in data engineering or software engineering, with a strong track record of delivering production-grade ELT/ETL pipelines for complex, regulated data domains

• Demonstrated expertise building fully automated, event-driven pipelines that operate without human intervention in steady state

• Proficiency in Python (primary) and/or Typescript or Java; advanced SQL; infrastructure-as-code (Terraform, AWS CDK, or equivalent)

• Deep, hands-on AWS experience: S3, Glue, Lambda, Step Functions, EventBridge, RDS - and the architectural judgment to choose the right service for the job

• Strong database design skills across relational and columnar stores - schema design, query optimization, partitioning, indexing

Clinical Data Standards

• Thorough, hands-on knowledge of CDISC (SDTM, ADaM, CDASH), FHIR, USDM, and ICH M11, and how controlled terminologies are implemented in practice across clinical trial workflows

• Proven fluency in terminology mapping - semantic alignment, code-list mapping, managing evolving and inconsistent terminologies across standards and source systems

• Practical understanding of how clinical dictionaries (MedDRA, WHO Drug, SNOMED, NCI Thesaurus, CDISC CT) are structured, versioned, and applied across the study lifecycle

AI/ML Application

• Experience applying AI or ML techniques to data engineering challenges - automated mappings, anomaly detection, intelligent quality checks, or NLP-based standards analysis

• Ability to evaluate and integrate LLM-based tools into engineering workflows where they add genuine, measurable value

Leadership & Communication

• Demonstrated ability to set technical direction and mentor engineers in a senior/lead capacity

• Exceptional communicator - able to influence cross-functional stakeholders and translate between engineering and clinical/regulatory domains

• Comfort operating in agile/scrum teams; fluent with Jira, Confluence, and related tooling

• Experience working in or alongside GxP-regulated environments, with understanding of validation, audit trail, and documentation requirements

Preferred Qualifications:

• Advanced degree (Master's or PhD) in Computer Science, Bioinformatics, Data Engineering, Life Sciences, or related field

• Direct pharma/biotech, CRO, or clinical technology experience, particularly in data standards or data engineering functions

• Familiarity with metadata repositories and standards governance processes (e.g., CDISC Library API, NCI EVS)

• Experience with additional standards: CDASH, SEND, HL7 v2/v3, OMOP CDM

• Background in platform or product engineering - thinking beyond pipelines to reusable services and APIs that teams consume

Why Evinova? Evinova sits at a rare intersection: the scientific credibility and scale of AstraZeneca, with the engineering culture and pace of a health tech company. You won't be maintaining legacy systems - you'll be building the infrastructure that defines how clinical data standards are consumed across an entire enterprise, with AI accelerating everything. * Real impact: Your pipelines will directly influence how clinical trial data is coded, analyzed, and submitted to regulators globally * Engineering-first culture: Automation, clean architecture, and technical craft are valued - not just delivery velocity * Global scale, startup pace: Work with a distributed, high-calibre team across multiple continents, with the resources of a top-5 global pharma behind you * Growth: Evinova is still building. The decisions you make now will shape the platform for years When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.